Atypical antipsychotics usage in long-term follow-up of first episode schizophrenia
Bibliographic record
Abstract
BACKGROUND: It is not clear if the role of antipsychotics in long-term clinical and functional recovery from schizophrenia is correlated. The pattern of use is a major aspect of pharmacotherapy in long-term follow-ups of schizophrenia. The aim of this study was to examine patterns of antipsychotic usage in patients with longstanding psychosis and their relationship to social outcomes. MATERIALS AND METHODS: We conducted a cross-sectional study on a cohort from a long-term outcome study. Participants were 116 first episode schizophrenia patients from Mumbai, India, who had more than 80% compliance, as reported by relatives. Patients were assessed on antipsychotic medication use and on clinical and functional parameters. RESULTS: There was a high compliance rate (72%). Most patients (77%) used atypical antipsychotics; only 10 (8.6%) patients were taking typical antipsychotics. There were no among-drug differences in the percentage of patients meeting the recommended dose: Clozapine (200-500 mg), Riseperidone (4.0-6.0 mg), Olanzapine (10-20 mg), Quetiapine (400-800 mg), Aripiprazole (15-30 mg), Ziprasidone (120-160 mg); an equivalent dosage of Chlorpromazine (300-600 mg) did not differ amongst any atypical antipsychotic subgroup. Also, we did not find any significant differences in recovery on Clinical Global Impression Severity scale (CGIS), Quality of Life (QOL), or Global Assessment of Functioning (GAF) between groups of antipsychotic drugs. CONCLUSION: This study shows that most patients suffering from schizophrenia, in a long-term follow-up, use prescribed atypical antipsychotics within the recommended limits. Also, the chlorpromazine equivalence dosages do not differ across antipsychotic medications. The outcomes on clinical and functional parameters are also similar across all second-generation antipsychotics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".